The invention pertains generally to the field of image processing, and, more particularly, to the field of generating quantifiable images from digital images representing data spatially as pixel patterns of greater and lesser intensity.
The preferred embodiment of the invention is adapted for analysis of biological data generated in recombinant DNA research and other biological research. Such data includes 2D gels, DNA sequencing gels, gel blots, RFLP, DNA blots, microtiter color, microtiter fluorescence and other types of data presented spatially in an image. Typically, such images consist of a plurality of pixels with areas of pixels of varying intensity representing some amount of a particular DNA or protein with the intensity attributable to the protein being superimposed upon intensity representing background noise and high frequency noise caused by such things as pinholes in the film, penetration of the film by gamma rays etc.
Although the invention will be described in terms of its application to biological data, it will be appreciated that the teachings of the invention have utility in other fields of analysis of images.
A problem in analyzing such data in the past so as to be able to quantify the amount of a protein represented by a particular area of pixels in the image has been how to separate the intensity representing the data from the intensity caused by background noise. Although pixel intensity is the concept used herein to convey the teachings of the invention, pixel value is the general concept contemplated by the teachings of the invention. That is, the pixel values being analyzed may represent something other than light intensity. For example, each pixel in an image may represent the strength of radio transmissions from a small sector of the sky such that the invention could be used in radio astronomy applications.
In the past, such techniques as rolling ball filters have been used for background noise removal from images. Such a teaching is found in a conference paper by Rutherford et al. entitled "Object Identification and Measurement from Images with Access to the Database to Select Specific Subpopulations of Special Interest" published at the E-O Lase and E-O Imaging Conference sponsored by S.P.I.E., January 1987 with the proceedings published in May of 1987. There, the authors describe a method of background correction, i.e., noise removal, by use of a rolling ball filter which effectively takes the minimum pixel value in the ball filter region as the pixel value for the background image. The resultant image is then subtracted from the digitized image. A pipeline image array processor is used to perform this process. Such a technique however is not optimized for removal of background noise and high frequency noise in all situations because it does not take into account the varying geometric shapes of the data of interest in many varied application and because it does not take into account other application specific phenomenon such as vertical noise strips, dead spaces etc.
Accordingly, a need has arisen for apparatus and a method to optimize the noise removal process for data presented in many varied spatial formats.